The Project
Palno and Slemon is a project designed to solve one of my most exhausting problems and serves as my entry for the Smart Home & Healthcare Challenge.
The core issue I am tackling is poor sleep quality. Sleeplessness isn't caused only by a lack of sleep; it is also heavily impacted by the sleep stage in which we wake up. This is why we sometimes feel completely refreshed despite fewer hours of sleep, yet feel exhausted even after sleeping for many hours.
While the most accurate way of detecting sleep stages is EEG, it isn't practical for daily personal use. After several days of research, I initially considered using blood oxygen levels and heartbeat tracking. However, realizing this alone wouldn't provide enough accuracy, I decided to also measure body movement using a mmWave radar sensor. Combining all these parameters will allow me to achieve a reasonable degree of accuracy, helping ensure I no longer wake up feeling tired.
Additionally, I am integrating a temperature sensor for smart climate control, which will optimize sleep quality even further and support the main goal of this project.
Project Architecture
Slemon
-
Main Brain: Arduino Uno Q (4GB) (A huge thanks to element14 for selecting me as a Top Tech Voices winner, which allowed me to get this!)
-
Temperature Sensing: MAX30208EVSYS board paired with the MAX32630FTHR microcontroller for precise 0.1°C accuracy. (Thank you for providing this in the kit!)
-
Display: 3.5-inch e-ink display to show information without causing eye strain.
-
Movement Sensing: HLK-LD2410 24GHz mmWave sensor. (Special thanks to @shabaz for the extremely helpful blog post!)
Palno
-
Wireless Transfer: ESP32 for compact, low-power data transmission.
-
Biometrics: MAXREFDES117 for precise SpO2 and BPM readings. (Thank you for adding this to the kit as well.)
All housed under the protection of 3M EM25TP-0050 EMI Absorber.
Implementation Plan
-
Phase 1: Configuring and validating every individual component before system integration.
-
Phase 2: Integrating the components together and writing basic firmware.
-
Phase 3: Sourcing, collecting, and labeling data, then building the algorithm to make the data usable.
-
Phase 4: Training the model and developing the final firmware.
-
Phase 5: System verification and performance validation.
-
Phase 6: Building the enclosure.
-
Phase 7 (Final post with Blog): Building the user interface in both LabVIEW and web interface.
The kit has arrived, and I will be posting the configuration and setup post soon.
(Sorry this post is rewritten by AI because there was and error coming while posting no matter what I did it was not resolving, but its generated from my original written plan. And because of it I had also not included images.)
Thank you for reading! Please let me know if you have any suggestions to make it even better.
